FUZZY EXPERT SYSTEMS APPLICATION IN HUMAN RESOURCES MANAGEMENT FOR META-COMPETENCIES AND LABOUR FORCES TO BE ESTIMATED

Abstract

The study showed that in the modern labor market, the competitive advantage of applicants is not only professional knowledge and skills but also a high level of meta-competencies, including critical thinking, emotional intelligence, creativity, and the ability to self-study. The paper discusses the importance of evaluating these skills. Their evaluation is still uncertain because they are not defined as part of professional standards and cannot be quantified. It has been revealed that traditional methods, such as tests and interviews, do not provide a sufficient assessment of the potential of applicants. The paper provides models of a fuzzy expert system that can evaluate applicant meta-competencies during recruitment, determine the learning trajectory, and assess the complexity of work performed. Fuzzy sets are employed in the approaches considered to take into account multiple factors that affect the development of meta-competitions and their interrelationship. The input parameters include variables like critical thinking, emotional intelligence, creativity, and self-learning, which are assigned different weights depending on the demands of a particular position. Fuzzy expert systems were used to evaluate the complexity of specific types of work and the time needed for their implementation, and the results are presented. The forecast error of these systems usually does not exceed 10%, making them an effective tool even without design and technical documentation or regulations. The potential of this approach in human resource management is bolstered by the use of fuzzy expert systems, which enable more accurate prediction of candidate success in the workplace.